Instructions to use jyp96/clock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/clock with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/clock") prompt = "A photo of sks clock in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cfc2f726489d9596875e31c51d1c1c2c39b7de747f05ee0273609e05ded674be
- Size of remote file:
- 19.1 MB
- SHA256:
- 258ca048b9b7cdbc2e362001f13b060b4d8d29b3a247293a28dd4bf51019dcca
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